Activity-Driven Computational Strategies of a Dynamically Regulated Integrate-and-Fire Model Neuron

Activity-dependent slow biochemical regulation processes, affecting intrinsic properties of a neuron, might play an important role in determining information processing strategies in the nervous system. We introduce second-order biochemical phenomena into a linear leaky integrate-and-fire model neuron together with a detailed kinetic description for synaptic signal transduction. In this framework, we investigate the membrane intrinsic electrical properties differentiation, showing the appearance of activity-dependent shifts between integration and temporal coincidence detection operating mode, for the single unit of a network.

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